{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "174d410a",
   "metadata": {},
   "source": [
    "# 创建散点图\n",
    "借助 Pyplot，您可以使用 scatter() 函数绘制散点图。\n",
    "\n",
    "scatter() 函数为每个观察绘制一个点。 它需要两个长度相同的数组，一个用于 x 轴的值，另一个用于 y 轴上的值："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a8924fb9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8445ebdd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.array([5,7,8,7,2,17,2,9,4,11,12,9,6])\n",
    "y = np.array([99,86,87,88,111,86,103,87,94,78,77,85,86])\n",
    "\n",
    "plt.scatter(x, y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04df7f48",
   "metadata": {},
   "source": [
    "# 颜色\n",
    "使用 color 或 c 参数为每个散点图设置自己的颜色："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c27f4e82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.array([5,7,8,7,2,17,2,9,4,11,12,9,6])\n",
    "y = np.array([99,86,87,88,111,86,103,87,94,78,77,85,86])\n",
    "plt.scatter(x, y, color = 'hotpink')\n",
    "\n",
    "x = np.array([2,2,8,1,15,8,12,9,7,3,11,4,7,14,12])\n",
    "y = np.array([100,105,84,105,90,99,90,95,94,100,79,112,91,80,85])\n",
    "plt.scatter(x, y, color = '#88c999')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76fd661b",
   "metadata": {},
   "source": [
    "# 给每个点上色\n",
    "可以通过使用颜色数组作为 c 参数的值来为每个点设置特定颜色，\n",
    "\n",
    "不能为此使用 color 参数，只能使用 c 参数。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e96fded6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.array([5,7,8,7,2,17,2,9,4,11,12,9,6])\n",
    "y = np.array([99,86,87,88,111,86,103,87,94,78,77,85,86])\n",
    "colors = np.array([\"red\",\"green\",\"blue\",\"yellow\",\"pink\",\"black\",\"orange\",\"purple\",\"beige\",\"brown\",\"gray\",\"cyan\",\"magenta\"])\n",
    "\n",
    "plt.scatter(x, y, c=colors)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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X7IFm9tawpThuAovIn7qdigoMNsg71AxMa8N8v7AItWBsDWyZ6J8ZV4qMyDuGPdLOvqOoMyQ04s4+ZKPTjLxWKpoeYJOf1+pUM6Kxvku6pjV9SisV5wfYIO/QNrmkHzwab9YyIqxa0ye3UPG0bjbIi2lGQW4L+fK62SCvZSiBsmRMbCbflC42BRObBTVjQjP5JnexKZigZYTliZJROH4bzZjUyQZ5MQdoYU4TzcjtYIO8HBnZTTRjQgebwmwtIyxPlIyicY1UMr6dDfJitknR2EYqyWljg7yWoQTKkpHVQCXZ29kUZTUIakZmA5WM3c6mKFPLCMsTJaM4YyuVZrWyQV7MAVo8up5Kx7SwQV6OjPQtVJrZzKY4fYuWYQuUJSOtjkoztrEpTqsT1IzUOipN38amOFXLCMsTJcOXspn8aU1skBdzN/ElbyL/qEY2yGsZSqAsGUm15E9pYONLqhXUDO9G8idvZePzbtQybIHCZNSQf2Q9G5+3RlAzEjeQP2kLG1/iBkEyPOvJn1jHxudZr2XYAmXJiF9L/oRNbHzxawU1w72G/J5aNj73Gi3DFihLxvDV5HdvZOMbvlpQM4ZVk39EDRvfsGotwxYoS8bQavIP38DGN1RSM+KqyD9sPRtfXJWgbTJ4Jfnj1rLxDV6pZdgCZcn4cSX5h6xh4/txpaBmXLOC/INXs/Fds0LLsAXKkvHD5eS/ppqN74fL5TSjeFAFlf5oFRvkxfynAi3js//7xir+wVIqHbSSDfJymvH9JVT6g0o2xd9fomXYAmXJuHoRlf7HcjbFVy8S1IzvLaTSq5exKf7eQjkyir6zgEq+u5QN8mIOUC0j4tZa9O2bqOQ7S9ggL6cZV5VTybcWsym6qlzLsAXKkvHNMiq5aiGbom+WRbsZoZk7aowExstgjkZUPqzCr8+nGd+4mQ3yUTwzMGkF16/C6r9g2IhjYq50GfZUFSy4DBNW1JQVxwREXsgq/NqNNOPrN7FBPlrNUNNWPlGPmMWzSzVlUOQinHpuFcTMJV9sORvkoyUDQ4cizgqsObIpTjkIX8ea6rqWClxz2CAfRRk5X9qZERcXd1At5KKxUpf6mrpO2LDDT3A3CQ0fUsPKorJFHP6Z9eW0AW3gK2zg/wHPelEj2rXYLwAAAABJRU5ErkJggg=="
    }
   },
   "cell_type": "markdown",
   "id": "853f6b6c",
   "metadata": {},
   "source": [
    "# 颜色图\n",
    "Matplotlib 模块有许多可用的颜色图。\n",
    "\n",
    "颜色图就像一个颜色列表，其中每种颜色都有一个范围从 0 到 100 的值。\n",
    "\n",
    "下面是一个颜色图的例子：\n",
    "\n",
    "![image.png](attachment:image.png)\n",
    "\n",
    "此颜色图称为“viridis”，如您所见，它的范围从 0（紫色）到 100（黄色）。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "776a6532",
   "metadata": {},
   "source": [
    "## 如何使用颜色图\n",
    "您可以使用带有颜色图值的关键字参数 cmap 指定颜色图，在本例中为“viridis”，它是 Matplotlib 中可用的内置颜色图之一。\n",
    "\n",
    "此外，您必须创建一个包含值（从 0 到 100）的数组，散点图中的每个点都有一个值："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "df19e882",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 通过 plt.colorbar() 语句在绘图中包含颜色图\n",
    "x = np.array([5,7,8,7,2,17,2,9,4,11,12,9,6])\n",
    "y = np.array([99,86,87,88,111,86,103,87,94,78,77,85,86])\n",
    "colors = np.array([0, 10, 20, 30, 40, 45, 50, 55, 60, 70, 80, 90, 100])\n",
    "\n",
    "plt.scatter(x, y, c=colors, cmap='viridis')\n",
    "\n",
    "plt.colorbar()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43579714",
   "metadata": {},
   "source": [
    "## 可用的颜色图\n",
    "可以选择的内置颜色图：\n",
    "<table>\n",
    "<tbody>\n",
    "<tr>\n",
    "<th>Name</th>\n",
    "<th>Reverse</th>\n",
    "<th>Name</th>\n",
    "<th>Reverse</th>\n",
    "<th>Name</th>\n",
    "<th>Reverse</th>\n",
    "<th>Name</th>\n",
    "<th>Reverse</th>\n",
    "<th>Name</th>\n",
    "<th>Reverse</th>\n",
    "<th>Name</th>\n",
    "<th>Reverse</th>\n",
    "<th></th>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Accent</td>\n",
    "<td>Accent_r</td>\n",
    "<td>Blues</td>\n",
    "<td>Blues_r</td>\n",
    "<td>BrBG</td>\n",
    "<td>BrBG_r</td>\n",
    "<td>BuGn</td>\n",
    "<td>BuGn_r</td>\n",
    "<td>BuPu</td>\n",
    "<td>BuPu_r</td>\n",
    "<td>CMRmap</td>\n",
    "<td>CMRmap_r</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Dark2</td>\n",
    "<td>Dark2_r</td>\n",
    "<td>GnBu</td>\n",
    "<td>GnBu_r</td>\n",
    "<td>Greens</td>\n",
    "<td>Greens_r</td>\n",
    "<td>Greys</td>\n",
    "<td>Greys_r</td>\n",
    "<td>OrRd</td>\n",
    "<td>OrRd_r</td>\n",
    "<td>Oranges</td>\n",
    "<td>Oranges_r</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>PRGn</td>\n",
    "<td>PRGn_r</td>\n",
    "<td>Paired</td>\n",
    "<td>Paired_r</td>\n",
    "<td>Pastel1</td>\n",
    "<td>Pastel1_r</td>\n",
    "<td>Pastel2</td>\n",
    "<td>Pastel2_r</td>\n",
    "<td>PiYG</td>\n",
    "<td>PiYG_r</td>\n",
    "<td>PuBu</td>\n",
    "<td>PuBu_r</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>PuBuGn</td>\n",
    "<td>PuBuGn_r</td>\n",
    "<td>PuOr</td>\n",
    "<td>PuOr_r</td>\n",
    "<td>PuRd</td>\n",
    "<td>PuRd_r</td>\n",
    "<td>Purples</td>\n",
    "<td>Purples_r</td>\n",
    "<td>RdBu</td>\n",
    "<td>RdBu_r</td>\n",
    "<td>RdGy</td>\n",
    "<td>RdGy_r</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>RdPu</td>\n",
    "<td>RdPu_r</td>\n",
    "<td>RdYlBu</td>\n",
    "<td>RdYlBu_r</td>\n",
    "<td>RdYlGn</td>\n",
    "<td>RdYlGn_r</td>\n",
    "<td>Reds</td>\n",
    "<td>Reds_r</td>\n",
    "<td>Set1</td>\n",
    "<td>Set1_r</td>\n",
    "<td>Set2</td>\n",
    "<td>Set2_r</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>Set3</td>\n",
    "<td>Set3_r</td>\n",
    "<td>Spectral</td>\n",
    "<td>Spectral_r</td>\n",
    "<td>Wistia</td>\n",
    "<td>Wistia_r</td>\n",
    "<td>YlGn</td>\n",
    "<td>YlGn_r</td>\n",
    "<td>YlGnBu</td>\n",
    "<td>YlGnBu_r</td>\n",
    "<td>YlOrBr</td>\n",
    "<td>YlOrBr_r</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>YlOrRd</td>\n",
    "<td>YlOrRd_r</td>\n",
    "<td>afmhot</td>\n",
    "<td>afmhot_r</td>\n",
    "<td>autumn</td>\n",
    "<td>autumn_r</td>\n",
    "<td>binary</td>\n",
    "<td>binary_r</td>\n",
    "<td>bone</td>\n",
    "<td>bone_r</td>\n",
    "<td>brg</td>\n",
    "<td>brg_r</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>bwr</td>\n",
    "<td>bwr_r</td>\n",
    "<td>cividis</td>\n",
    "<td>cividis_r</td>\n",
    "<td>cool</td>\n",
    "<td>cool_r</td>\n",
    "<td>coolwarm</td>\n",
    "<td>coolwarm_r</td>\n",
    "<td>copper</td>\n",
    "<td>copper_r</td>\n",
    "<td>cubehelix</td>\n",
    "<td>cubehelix_r</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>flag</td>\n",
    "<td>flag_r</td>\n",
    "<td>gist_earth</td>\n",
    "<td>gist_earth_r</td>\n",
    "<td>gist_gray</td>\n",
    "<td>gist_gray_r</td>\n",
    "<td>gist_heat</td>\n",
    "<td>gist_heat_r</td>\n",
    "<td>gist_ncar</td>\n",
    "<td>gist_ncar_r</td>\n",
    "<td>gist_rainbow</td>\n",
    "<td>gist_rainbow_r</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>gist_stern</td>\n",
    "<td>gist_stern_r</td>\n",
    "<td>gist_yarg</td>\n",
    "<td>gist_yarg_r</td>\n",
    "<td>gnuplot</td>\n",
    "<td>gnuplot_r</td>\n",
    "<td>gnuplot2</td>\n",
    "<td>gnuplot2_r</td>\n",
    "<td>gray</td>\n",
    "<td>gray_r</td>\n",
    "<td>hot</td>\n",
    "<td>hot_r</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>hsv</td>\n",
    "<td>hsv_r</td>\n",
    "<td>inferno</td>\n",
    "<td>inferno_r</td>\n",
    "<td>jet</td>\n",
    "<td>jet_r</td>\n",
    "<td>magma</td>\n",
    "<td>magma_r</td>\n",
    "<td>nipy_spectral</td>\n",
    "<td>nipy_spectral_r</td>\n",
    "<td>ocean</td>\n",
    "<td>ocean_r</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>pink</td>\n",
    "<td>pink_r</td>\n",
    "<td>plasma</td>\n",
    "<td>plasma_r</td>\n",
    "<td>prism</td>\n",
    "<td>prism_r</td>\n",
    "<td>rainbow</td>\n",
    "<td>rainbow_r</td>\n",
    "<td>seismic</td>\n",
    "<td>seismic_r</td>\n",
    "<td>spring</td>\n",
    "<td>spring_r</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>summer</td>\n",
    "<td>summer_r</td>\n",
    "<td>tab10</td>\n",
    "<td>tab10_r</td>\n",
    "<td>tab20</td>\n",
    "<td>tab20_r</td>\n",
    "<td>tab20b</td>\n",
    "<td>tab20b_r</td>\n",
    "<td>tab20c</td>\n",
    "<td>tab20c_r</td>\n",
    "<td>terrain</td>\n",
    "<td>terrain_r</td>\n",
    "</tr>\n",
    "<tr>\n",
    "<td>twilight</td>\n",
    "<td>twilight_r</td>\n",
    "<td>twilight_shifted</td>\n",
    "<td>twilight_shifted_r</td>\n",
    "<td>viridis</td>\n",
    "<td>viridis_r</td>\n",
    "<td>winter</td>\n",
    "<td>winter_r</td>\n",
    "</tr>\n",
    "</tbody>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0a868d1",
   "metadata": {},
   "source": [
    "# 尺寸\n",
    "使用 s 参数更改点的大小。\n",
    "\n",
    "就像颜色一样，确保大小数组的长度与 x 和 y 轴的数组长度相同："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7739d770",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.array([5,7,8,7,2,17,2,9,4,11,12,9,6])\n",
    "y = np.array([99,86,87,88,111,86,103,87,94,78,77,85,86])\n",
    "sizes = np.array([20,50,100,200,500,1000,60,90,10,300,600,800,75])\n",
    "\n",
    "plt.scatter(x, y, s=sizes)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f089e7e3",
   "metadata": {},
   "source": [
    "# 透明度\n",
    "您可以使用 alpha 参数调整点的透明度。\n",
    "\n",
    "就像颜色一样，确保大小数组的长度与 x 和 y 轴的数组长度相同："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9183aac9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.array([5,7,8,7,2,17,2,9,4,11,12,9,6])\n",
    "y = np.array([99,86,87,88,111,86,103,87,94,78,77,85,86])\n",
    "sizes = np.array([20,50,100,200,500,1000,60,90,10,300,600,800,75])\n",
    "\n",
    "plt.scatter(x, y, s=sizes, alpha=0.5)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40417e63",
   "metadata": {},
   "source": [
    "# 组合颜色、大小和透明度\n",
    "在点上组合具有不同大小的颜色图。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "dc22916b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.random.randint(100, size=(100))\n",
    "y = np.random.randint(100, size=(100))\n",
    "colors = np.random.randint(100, size=(100))\n",
    "sizes = 10 * np.random.randint(100, size=(100))\n",
    "\n",
    "plt.scatter(x, y, c=colors, s=sizes, alpha=0.5, cmap='nipy_spectral')\n",
    "\n",
    "plt.colorbar()\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.10"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
